Ultramodern Underground Dallas: Vincent Ponte’s Pedestrian-Way as Systematic Solution to the Declining Downtown
Bibliographic record
Abstract
Mid last century, North American civil servants and urban planners and developers proffered inventive solutions to the problem of the declining downtown core. Robert Moses looked to super-block development and Title 1 of the US Housing Act of 1949 to funnel federal dollars into urban renewal projects in New York City. Because it had been successful in the suburbs, Victor Gruen sought retail development in the form of downtown shopping centres. The Montreal-based planner Vincent Ponte focused his attention on the “multi-level city centre.” Similar to the solutions proffered by Gruen and Moses, Ponte’s multi-level centres were large-scale and multi-use. However, unlike his colleagues’ tabula rasa interventions, Ponte’s multi-level centre was incremental. This essay focuses on Ponte’s little-known 1969 multi-level pedestrian-way plan for downtown Dallas. I argue that Ponte’s project for the centre of Dallas is unique in Ponte’s oeuvre because, departing from his own espousal of super-block development, it was not built in one fell swoop within a super-block. The multi-level megastructural pedestrian-way in Dallas was fluid and incremental in its original planning and subsequent evolution. It is best understood according to Ponte’s instrumentalization of systems theory.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".